Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947096
Xue Xu, Tao Jing
Strong Signal Masking is an anti-interception technology that covers the effective signal by using known signals with strong power characteristics, which not only ensures receiving accuracy of cooperators, but also increases receiving difficulty of non-cooperators and reduces accuracy of intercepted data. In this paper, Strong Signal Masking is combined with Orthogonal Frequency Division Multiplexing (OFDM) and anti-intercepting transmission scheme in physical layer is taken as the research direction. The paper focuses on bit error rate (BER) of effective signals under the cover of known signals as well as similarity of data intercepted by non-cooperators. Random data and Preamble data are used as known signals respectively for hidden transmission of effective data. In addition, preamble sequence data mirroring masking mechanism is proposed to reduce the BER of effective data. Simulation results show that BER performance of preamble sequence data mirroring masking system is greatly improved with the same similarity of data intercepted.
强信号掩蔽(Strong Signal Masking)是一种利用具有强功率特性的已知信号覆盖有效信号的反截获技术，既保证了合作方的接收精度，又增加了非合作方的接收难度，降低了截获数据的精度。本文将强信号掩蔽技术与正交频分复用技术(OFDM)相结合，以物理层防拦截传输方案为研究方向。本文重点研究了已知信号掩盖下有效信号的误码率以及非合作截获数据的相似度。随机数据和前置数据分别作为已知信号，用于隐藏有效数据的传输。此外，提出了前导序列数据镜像掩蔽机制，以降低有效数据的误码率。仿真结果表明，在截获数据相似度相同的情况下，前导序列数据镜像掩蔽系统的误码率性能得到了很大的提高。
{"title":"Design of Strong Signal Masking Covert Communication Transmission Scheme Based on OFDM System","authors":"Xue Xu, Tao Jing","doi":"10.1109/ICCT46805.2019.8947096","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947096","url":null,"abstract":"Strong Signal Masking is an anti-interception technology that covers the effective signal by using known signals with strong power characteristics, which not only ensures receiving accuracy of cooperators, but also increases receiving difficulty of non-cooperators and reduces accuracy of intercepted data. In this paper, Strong Signal Masking is combined with Orthogonal Frequency Division Multiplexing (OFDM) and anti-intercepting transmission scheme in physical layer is taken as the research direction. The paper focuses on bit error rate (BER) of effective signals under the cover of known signals as well as similarity of data intercepted by non-cooperators. Random data and Preamble data are used as known signals respectively for hidden transmission of effective data. In addition, preamble sequence data mirroring masking mechanism is proposed to reduce the BER of effective data. Simulation results show that BER performance of preamble sequence data mirroring masking system is greatly improved with the same similarity of data intercepted.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124259236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Various pioneering human posture recognition techniques based on Channel State Information (CSI) of WiFi devices have been proposed. The main issue of existing techniques, however, lies in such recognition methods are extremely sensitive to the impacts of random noise derived from indoor environments. In this paper, we present a fine-grained human posture recognition (FiPR) scheme to overcome this issue by extracting two unique statistics features in CSI profile, including mutual information (MI) and cross correlation (CC). In order to eliminate the influences of noise components on the recognition accuracy, a corresponding Discrete Wavelet Transform (DWT) strategy is introduced to denoise by using signal decomposition. Furthermore, FiPR can recognize four basic human postures by measuring the correlation between a given unknown posture and pre-constructed postures profiles. Compared with existing Doppler-based recognition methods, the recognition accuracy of the proposed FiPR scheme can be improved effectively. We implement FiPR scheme on the commercial WiFi devices and evaluate its overall performance in a typical indoor environment. Experiment results demonstrate that our prototype can estimate human posture recognition with average accuracy of 95%.
{"title":"FiPR: A Fine-grained Human Posture Recognition","authors":"Jianyang Ding, Yong Wang, Yinghua Qi, Chengcheng Ma, Yuan Leng","doi":"10.1109/ICCT46805.2019.8947112","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947112","url":null,"abstract":"Various pioneering human posture recognition techniques based on Channel State Information (CSI) of WiFi devices have been proposed. The main issue of existing techniques, however, lies in such recognition methods are extremely sensitive to the impacts of random noise derived from indoor environments. In this paper, we present a fine-grained human posture recognition (FiPR) scheme to overcome this issue by extracting two unique statistics features in CSI profile, including mutual information (MI) and cross correlation (CC). In order to eliminate the influences of noise components on the recognition accuracy, a corresponding Discrete Wavelet Transform (DWT) strategy is introduced to denoise by using signal decomposition. Furthermore, FiPR can recognize four basic human postures by measuring the correlation between a given unknown posture and pre-constructed postures profiles. Compared with existing Doppler-based recognition methods, the recognition accuracy of the proposed FiPR scheme can be improved effectively. We implement FiPR scheme on the commercial WiFi devices and evaluate its overall performance in a typical indoor environment. Experiment results demonstrate that our prototype can estimate human posture recognition with average accuracy of 95%.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116654312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947031
Han Yu Lao
Aiming at the problem of unreliable data collection resulting from the limited resource of nodes in RWSN (Resource-constrained Wireless Sensor Network), this paper proposes a path planning algorithm for mobile device based on greedy strategy, abbreviated as PPGS. The monitoring area is divided into multiple regular hexagonal visiting units based on the charging radius of mobile device, and greedy strategy is used to plan the movement path of mobile device. Simulation results show that the PPGS algorithm can guarantee reliable energy supplement and data collection with a small number of mobile devices in RWSN.
{"title":"A Path Planning Algorithm of Mobile Device in RWSN","authors":"Han Yu Lao","doi":"10.1109/ICCT46805.2019.8947031","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947031","url":null,"abstract":"Aiming at the problem of unreliable data collection resulting from the limited resource of nodes in RWSN (Resource-constrained Wireless Sensor Network), this paper proposes a path planning algorithm for mobile device based on greedy strategy, abbreviated as PPGS. The monitoring area is divided into multiple regular hexagonal visiting units based on the charging radius of mobile device, and greedy strategy is used to plan the movement path of mobile device. Simulation results show that the PPGS algorithm can guarantee reliable energy supplement and data collection with a small number of mobile devices in RWSN.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117190386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The current maximum fault-tolerant tile mining has the following problems: 1) the mining speed is slow 2) the mining speed is greatly affected by the tolerance. To solve these problems, a maximum fault-tolerant tile-mining algorithm based on parallel PSO is proposed in this paper. PSO algorithm is used to find the maximum fault-tolerant tile quickly and accurately, and the Spark framework is combined to further improve the calculation speed. Compared with the maximum fault-tolerant tile mining algorithm of integer linear programming, experimental results are superior to traditional algorithms in speed and stability. Then the proposed algorithm was applied to wind power generation system, and the experiment outcome shows that the algorithm is accurate and eddective for the dateset of real system.
{"title":"Maximum Fault Tolerant Tile Mining Algorithm Based on Parallel PSO","authors":"Zhixiang Li, Hongmei Zhang, Xiangli Zhang, Dongsheng Qi","doi":"10.1109/ICCT46805.2019.8947145","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947145","url":null,"abstract":"The current maximum fault-tolerant tile mining has the following problems: 1) the mining speed is slow 2) the mining speed is greatly affected by the tolerance. To solve these problems, a maximum fault-tolerant tile-mining algorithm based on parallel PSO is proposed in this paper. PSO algorithm is used to find the maximum fault-tolerant tile quickly and accurately, and the Spark framework is combined to further improve the calculation speed. Compared with the maximum fault-tolerant tile mining algorithm of integer linear programming, experimental results are superior to traditional algorithms in speed and stability. Then the proposed algorithm was applied to wind power generation system, and the experiment outcome shows that the algorithm is accurate and eddective for the dateset of real system.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127136072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947087
Qiang Li, Yawen Lan, Daogang Lu, Jia Sun
Since the node duty cycle and backoff mechanism cannot change with the network environment, the power consumption of the S-MAC protocol is somewhat high. In the backoff phase, channel utilization is introduced to reflect the busyness of the network. In this paper, the size of the contention window of the node is adaptively adjusted, and the additional energy consumption caused by the network conflict is reduced by introducing the residual energy factor of the node. At the same time, in order to adapt to the dynamic changes of the network, the network traffic load factor is used to adaptively adjust the duty cycle of each node in the listening/sleep phase. This approach effectively increases network throughput and extends the lifecycle of the entire wireless sensor network. The simulation results depict that the proposed algorithm shows superior performance in terms of average network throughput, average latency, energy utilization, and adaptability over the S-MAC.
{"title":"Research on Improved S-MAC Energy Conservation Based on Adaptive Mechanism","authors":"Qiang Li, Yawen Lan, Daogang Lu, Jia Sun","doi":"10.1109/ICCT46805.2019.8947087","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947087","url":null,"abstract":"Since the node duty cycle and backoff mechanism cannot change with the network environment, the power consumption of the S-MAC protocol is somewhat high. In the backoff phase, channel utilization is introduced to reflect the busyness of the network. In this paper, the size of the contention window of the node is adaptively adjusted, and the additional energy consumption caused by the network conflict is reduced by introducing the residual energy factor of the node. At the same time, in order to adapt to the dynamic changes of the network, the network traffic load factor is used to adaptively adjust the duty cycle of each node in the listening/sleep phase. This approach effectively increases network throughput and extends the lifecycle of the entire wireless sensor network. The simulation results depict that the proposed algorithm shows superior performance in terms of average network throughput, average latency, energy utilization, and adaptability over the S-MAC.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124939292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947217
Kai Zhang, Yongsheng Xia, Yang Xia, Feng Ye
Storage Engine is the core of the storage system, R/W performance (read and write performance) of the storage system depends on the performance of the storage engine. sLSM-Tree structure (LSM-Tree structure based on the segmented index) is proposed, which is based on the structure of LevelDB. Segmented index structure is introduced to solve the collisions brought by adding hash storage RAM index structure to the index structure parts of LSM-Tree, i.e. trie index and hash index segmentally. By this way, index speed is improved and the pressure of updating index terms by compacting is reduced. The contrast experiment was conducted about the novel segmented index method presented in this paper. From the analysis of experimental results, sLSM-Tree has a significant performance in the RAM index and R/W operation on the hard disk compared with LevelDB which uses conventional LSM-Tree storage engine.
{"title":"An Optimization of Key-Value Store Based on Segmented LSM-Tree","authors":"Kai Zhang, Yongsheng Xia, Yang Xia, Feng Ye","doi":"10.1109/ICCT46805.2019.8947217","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947217","url":null,"abstract":"Storage Engine is the core of the storage system, R/W performance (read and write performance) of the storage system depends on the performance of the storage engine. sLSM-Tree structure (LSM-Tree structure based on the segmented index) is proposed, which is based on the structure of LevelDB. Segmented index structure is introduced to solve the collisions brought by adding hash storage RAM index structure to the index structure parts of LSM-Tree, i.e. trie index and hash index segmentally. By this way, index speed is improved and the pressure of updating index terms by compacting is reduced. The contrast experiment was conducted about the novel segmented index method presented in this paper. From the analysis of experimental results, sLSM-Tree has a significant performance in the RAM index and R/W operation on the hard disk compared with LevelDB which uses conventional LSM-Tree storage engine.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123597149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947014
Hamed Z. Jahromi, D. Delaney, Andrew Hines
Modelling Web Quality of Experience (QoE) using technical quality metrics has received much attention over the past years and has become an important part of network QoE monitoring and management studies. Mapping Web QoE metrics (e.g. MOS) to application metrics (e.g. waiting time) and network QoS metrics (e.g delay) helps to quantify the influence of different factor on the perceived quality. The literature shows that network delays can result in significantly longer loading times for web browsing and consequently impact the user’s perceived quality. We investigate the impact of network delay on the measurement of application quality metrics for three browsers and three operating systems using a web mapping application for our experimental tests. We then analyse how the choice of browser and operating system influences application level quality metrics. We demonstrate how time instant quality metrics measurement vary depending on the operating system due to TCP Retransmition TimeOut (RTO). Finally, we publish the collected data for the future studies.
{"title":"Quantifying the Influence of Browser, OS and Network Delay on Time Instant Metric Measurements for a Web Mapping Application","authors":"Hamed Z. Jahromi, D. Delaney, Andrew Hines","doi":"10.1109/ICCT46805.2019.8947014","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947014","url":null,"abstract":"Modelling Web Quality of Experience (QoE) using technical quality metrics has received much attention over the past years and has become an important part of network QoE monitoring and management studies. Mapping Web QoE metrics (e.g. MOS) to application metrics (e.g. waiting time) and network QoS metrics (e.g delay) helps to quantify the influence of different factor on the perceived quality. The literature shows that network delays can result in significantly longer loading times for web browsing and consequently impact the user’s perceived quality. We investigate the impact of network delay on the measurement of application quality metrics for three browsers and three operating systems using a web mapping application for our experimental tests. We then analyse how the choice of browser and operating system influences application level quality metrics. We demonstrate how time instant quality metrics measurement vary depending on the operating system due to TCP Retransmition TimeOut (RTO). Finally, we publish the collected data for the future studies.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115017481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947234
Wang Huan, Peng Cao, Fangfang Chen, Luo Wenqiu
In this paper, an improved algorithm of error diffusion is provided, which is better than the traditional error diffusion algorithm in processing image boundary, contour and texture details. It can make the outline of printed image more clear and display better under the same print equipment or print-arts conditions. Based on the original error diffusion algorithm, this algorithm extracts and enhances the edge contour and texture feature of halftone images, optimized the error diffusion algorithm. The result has the best matching of the display effect of the printed image in the smooth part and the edge contour part.
{"title":"Research on Error Diffusion Algorithms Based on Digital Image Feature Matching","authors":"Wang Huan, Peng Cao, Fangfang Chen, Luo Wenqiu","doi":"10.1109/ICCT46805.2019.8947234","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947234","url":null,"abstract":"In this paper, an improved algorithm of error diffusion is provided, which is better than the traditional error diffusion algorithm in processing image boundary, contour and texture details. It can make the outline of printed image more clear and display better under the same print equipment or print-arts conditions. Based on the original error diffusion algorithm, this algorithm extracts and enhances the edge contour and texture feature of halftone images, optimized the error diffusion algorithm. The result has the best matching of the display effect of the printed image in the smooth part and the edge contour part.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115582755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947252
Kun Yao, Jibin Yang, Xiongwei Zhang, Changyan Zheng, Xin Zeng
In recent years, increasing number of acoustic scene classification (ASC) methods are based on deep learning models. In these models, the extraction of robust deep feature plays an important role on the classification accuracy. However the complex combination of acoustic phenomena in an acoustic scene results in overlapping of the analysis features, which degrades the performance of ASC. To enhance the compactness of feature and fit the multi-classification task, we explored the data label learning for deep feature extraction. And we combined the method of label smoothing(LS) and the additive margin softmax loss (AM-softmax) to extract deep feature based on VGG-style deep neural network. The comparison experiments show that the best classification results are obtained by the proposed method, which accuracy on ESC-50 dataset is 81.9%, which is beyond human performance.
{"title":"Robust Deep Feature Extraction Method for Acoustic Scene Classification","authors":"Kun Yao, Jibin Yang, Xiongwei Zhang, Changyan Zheng, Xin Zeng","doi":"10.1109/ICCT46805.2019.8947252","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947252","url":null,"abstract":"In recent years, increasing number of acoustic scene classification (ASC) methods are based on deep learning models. In these models, the extraction of robust deep feature plays an important role on the classification accuracy. However the complex combination of acoustic phenomena in an acoustic scene results in overlapping of the analysis features, which degrades the performance of ASC. To enhance the compactness of feature and fit the multi-classification task, we explored the data label learning for deep feature extraction. And we combined the method of label smoothing(LS) and the additive margin softmax loss (AM-softmax) to extract deep feature based on VGG-style deep neural network. The comparison experiments show that the best classification results are obtained by the proposed method, which accuracy on ESC-50 dataset is 81.9%, which is beyond human performance.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128790821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/ICCT46805.2019.8947025
Xiaoyan Kuai, Xiaojun Yuan, Wenjing Yan
In this paper, we study joint device activity identification, channel estimation, and signal detection for the uplink transmission of a human-type communication (HTC) and machine-type communication (MTC) coexisted massive MIMO system. We first establish a probability model to characterize the crucial system features including channel sparsity of massive MIMO, signal sparsity of MTC packets, and sporadic access of MTC. With the probability model, we formulate a blind detection problem and establish a factor graph representation of the problem. Based on that, we develop a turbo message passing (TMP) algorithm involving affine sparse matrix factorization and service type identification. We show that our proposed blind detection algorithm significantly outperform their counterpart algorithms including the training-based algorithm.
{"title":"Blind Detection in Coexistence of Human-Type and Machine-Type Communications","authors":"Xiaoyan Kuai, Xiaojun Yuan, Wenjing Yan","doi":"10.1109/ICCT46805.2019.8947025","DOIUrl":"https://doi.org/10.1109/ICCT46805.2019.8947025","url":null,"abstract":"In this paper, we study joint device activity identification, channel estimation, and signal detection for the uplink transmission of a human-type communication (HTC) and machine-type communication (MTC) coexisted massive MIMO system. We first establish a probability model to characterize the crucial system features including channel sparsity of massive MIMO, signal sparsity of MTC packets, and sporadic access of MTC. With the probability model, we formulate a blind detection problem and establish a factor graph representation of the problem. Based on that, we develop a turbo message passing (TMP) algorithm involving affine sparse matrix factorization and service type identification. We show that our proposed blind detection algorithm significantly outperform their counterpart algorithms including the training-based algorithm.","PeriodicalId":306112,"journal":{"name":"2019 IEEE 19th International Conference on Communication Technology (ICCT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128287596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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